Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use thenlper/gte-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use thenlper/gte-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("thenlper/gte-base") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
Add exported onnx model 'model_qint8_avx512_vnni.onnx'
#12
by tomaarsen HF Staff - opened
onnx/model_qint8_avx512_vnni.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:2587e6c23fa6333f81997b6bc3571df2c000fc96f7a5bd2c1158d9af0891e976
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size 110121976
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